Using workflows to explore and optimise named entity recognition for chemistry

PLoS ONE

Volumn 6, Issue 5, 2011, Pages

  Kolluru, BalaKrishna ^a   Hawizy, Lezan ^b   Murray Rust, Peter ^b   Tsujii, Junichi ^a   Ananiadou, Sophia ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ANALYTICAL ERROR; ARTICLE; AUTOMATION; CHEMICAL ANALYSIS; CHEMISTRY; CLASSIFIER; COMPUTER INTERFACE; COMPUTER SYSTEM; DATA MINING; ENTROPY; NOMENCLATURE; SCORING SYSTEM; ALGORITHM; BIOLOGY; MEDLINE; METHODOLOGY; NATURAL LANGUAGE PROCESSING; PROBABILITY; REPRODUCIBILITY; WORKFLOW;

ALGORITHMS; CHEMISTRY; COMPUTATIONAL BIOLOGY; MARKOV CHAINS; NATURAL LANGUAGE PROCESSING; PUBMED; REPRODUCIBILITY OF RESULTS; TERMINOLOGY AS TOPIC; WORKFLOW;

EID: 79957462120     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0020181     Document Type: Article

References (47)

1. Kemp N, Lynch M, (1998) Extraction of information from the text of chemical patents. 1. identification of specific chemical names. Journal of Chemical Information and Computer Sciences 4: 544-551.
2. Murray-Rust P, Rzepa H, (1999) Chemical markup, xml, and the worldwide web. 1. basic principles. Journal of Chemical Information and Computer Sciences 39: 928-942.
3. Murray-Rust P, Mitchell J, Rzepa H, (2005) Chemistry in bioinformatics. BMC Bioinformatics 6: 141.
4. Banville D, (2006) Mining chemical structural information from the drug literature. Drug Discovery Today 11: 35-42.
5. Kolrik C, Hofmann-Apitius M, Zimmermann M, Fluck J, (2007) Identification of new drug classification terms in textual resources. Bioinformatics 13: 264-272.
6. Miyao Y, Tsujii J, (2005) Probabilistic disambiguation models for wide-coverage hpsg parsing. ACL-2005 pp. 83-90.
7. Tsuruoka Y, Tateishi Y, Kim J, Ohta T, McNaught J, et al. (2005) Developing a robust part-ofspeech tagger for biomedical text. In: Bozanis P, Houstis EN, editors. volume 3746, chapter 36 Berlin Heidelberg Advances in Informatics, Springer: 382-392 doi:http://dx.doi.org/10.1007/11573036.
8. Steinbeck C, Hoppe C, Kuhn S, Floris M, Guha R, et al. (2006) Recent developments of thechemistry development kit (cdk)- an open-source java library for chemo- and bioinformatics. Current Pharmaceutical Design pp. 2111-2120.
9. Corbett P, Murray-Rust P, (2006) High-throughput identification of chemistry in life science texts.In: Computational Life Sciences II. pp. 107-118 doi:http://dx.doi.org/10.1007/11875741_11.
10. Wren J, (2006) A scalable machine learning approach to recognize chemical names within large textdatabases. BMC Bioinformatics 7: S3.
11. Florian B, Juan MTM, El-Bèze M, (2008) Mixing statistical and symbolic approaches for chemicalnames recognition. In: CICLing pp. 334-343.
12. Klinger R, Kolarik C, Fluck J, Hofmann-Apitius M, Friedrich C, (2008) Detection of IUPAC and IUPAC-like Chemical Names. Bioinformatics 24: i268-276.
13. Jiao D, Wild DJJ, (2009) Extraction of cyp chemical interactions from biomedical literature using natural language processing methods. Journal of chemical information and modeling 49: 263-269.
14. Hettne K, Stierum R, Schuemie M, Hendriksen P, Schijvenaars B, et al. (2009) A dictionary to identify small molecules and drugs in free text. Bioinformatics 25: 2983-2991.
15. Hettne K, Williams A, van Mulligen E, Kleinjans J, Tkachenko V, et al. (2010) Automatic vs. manual curation of a multi-source chemical dictionary: The impact on text mining. Journal of Cheminformatics 2: 4.
16. Kolarik C, Klinger R, Friedrich C, Hofmann-Apitius M, Fluck J, (2008) Chemical names: Terminological resources and corpora annotation. In: Workshop on Building and evaluating resources for biomedical text mining, 6th edition LREC.
17. Klinger R, Friedrich C, Hofmann-Apitius M, Fluck J, Birlinghoven S, (2009) Chemical names: Terminological resources and corpora annotation.
18. Muller B, Klinger R, Gurulingappa H, Mevissen H, Hofmann-Apitius M, et al. (2010) Abstractsversus full texts and patents: A quantitative analysis of biomedical entities Advances in Multidisciplinary Retrieval volume 6107, chapter 12 Berlin, Heidelberg Springer Berlin Heidelberg,: 152-165 doi:http://dx.doi.org/10.1007/978-3-642-13084-7_12.
19. Rupp CJ, Copestake A, Corbett P, Waldron B, (2007) Integrating general-purpose and domainspecific components in the analysis of scientific text.
20. Hassan M, Brown R, Varma-O'brien S, Rogers D, (2006) Cheminformatics analysis and learning in a data pipelining environment. Molecular diversity 10: 283-299.
21. Tiwari A, Sekhar A, (2008) Workflow based framework for life science informatics. Computational Biology and Chemistry 31: 306-319.
22. Shon J, Ohkawa H, Hammer J, (2008) Scientific workflows as productivity tools for drug discovery. Current opinion in drug discovery and development 11: 381-388.
23. Kuhn T, Willighagen E, Zielesny1 A, Steinbeck C, (2010) Cdk-taverna: An open workflow environment for cheminformatics. Bioinformatics 11.
24. Kano Y, Baumgartner W, McCrohon L, Ananiadou S, Cohen K, et al. (2009) U-compare: Share and compare text mining tools with uima. Bioinformatics 25: 1997-1998.
25. Ferrucci D, Lally A, Gruhl D, Epstein E, Schor M, et al. (2006) Towards an interoperabilitystandard for text and multi-modal analytics. Technical report, IBM.
26. Apache, (2010) Unstructured information management. URL http://uima.apache.org/. [last accessed on 02-May-2011].
27. Tsuruoka Y, Tsujii J, Ananiadou S, (2009) Fast full parsing by linear-chain conditional random fields. In: EACL '09: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics. Morristown, NJ, USA Association for Computational Linguistics pp. 790-798.
28. OpenNLP (2010) Opennlp. URL http://incubator.apache.org/opennlp/. [last accessed on 02-May-2011].
29. Taylor I, Deelman E, Gannon D, Shields ME, (2007) Workflows for e-Science: Scientific Workflows for Grids. Springer.
30. Kuhn T, Zielesny A, Steinbeck C, (2009) Creating chemo- and bioinformatics workflows, further developments within the cdk-taverna project. Chemistry Central Journal 3: 42.
31. Oinn T, Addis M, Ferris J, Marvin D, Senger M, et al. (2004) Taverna: A tool for the composition and enactment of bioinformatics workflows. Bioinformatics 20: 3045-3054.
32. Ludascher B, Altintas I, Berkley C, Higgins D, Jaeger-Frank E, et al. (2006) Scientific workflow management and the kepler system. Special Issue: Workflow in Grid Systems Concurrency and Computation: Practice & Experience 18: 1039-1065.
33. Accelrys' (2010) Pipeline pilot. URL http://accelrys.com/products/pipeline-pilot/. [last accessed on 02-May-2011].
34. Vellay SG, Latimer ME, Paillard G, (2009) Interactive text mining with pipeline pilot: A bibliographic web-based tool for pubmed. Infectious disorders drug targets 9: 366-374.
35. Mellebeek B, Rodriguez-Penagos C, Furlong LI, (2009) Uima in the biocuration workflow: A coherent framework for cooperation between biologists and computational linguists. Nature Precedings.
36. Kano Y, N N, R S, Fukamachi K, Kazuhiro Y, et al. (2008) Sharable type system design for tool inter-operability and combinatorial comparison. In: Proceedings of the First International Conference on Global Interoperability for Language Resources (ICGL). Hong Kong, 122-129.
37. Kano Y, Dobson P, Nakanishi JM, Tsujii, Ananiadou S, (2010) Text mining meets workflow: Linking u-compare with taverna. Bioinformatics.
38. Townsend JA, Downing J, Murray-Rust P, (2009) Chic- converting hamburgers into cows. In: Proceedings of the 2009 Fifth IEEE International Conference on e-Science. Washington, DC, USA IEEE Computer Society, E-SCIENCE '09 pp. 337-343 doi:http://dx.doi.org/10.1109/e-Science http://dx.doi.org/10.1109/e-Science.2009.54.
39. Wilbur WJ, Hazard GF, Divita G, Mork JG, Aronson AR, et al. (1999) Analysis of biomedical text for chemical names: A comparison of three methods. AMIA Symposium pp. 176-180.
40. Rupp CJ, Copestake A, Teufel S, Waldron B, (2006) Flexible interfaces in the application of language technology to an escience corpus. In: Proceedings of the 4th UK E-Science All Hands Meeting (AHM2006).
41. Corbett P, Copestake A, (2008) Cascaded classifiers for confidence-based chemical named entity recognition. BMC Bioinformatics 9: S4.
42. Copestake A, Teufel S, Murray-Rust P, Parker A, (2010) Extracting the science from scientific publications. URL http://www.cl.cam.ac.uk/research/nl/sciborg/www/. [last accessed on 02-May-2011].
43. NIH (2010) Pubmed. URL http://www.ncbi.nlm.nih.gov/pubmed/. [last accessed on 02-May-2011].
44. EBI (2010) Chemical entities of biological interest (chebi). URL http://www.ebi.ac.uk/chebi/. [last accessed on 02-May-2011].
45. Kano Y, McCrohon L, Ananiadou S, Tsujii J, (2009) Integrated nlp evaluation system for pluggable evaluation metrics with extensive interoperable toolkit. In: SETQA-NLP '09: Proceedings of the Workshop on Software Engineering, Testing, and Quality Assurance for Natural Language Processing. Morristown, NJ Association for Computational Linguistics pp. 22-30.
46. Medline (2010) Medline. URL http://www.nlm.nih.gov/databases/databases_medline.html. [last accessed on 02-May-2011].
47. Nobata C, Sasaki Y, Okazaki N, Rupp CJ, Tsujii J, et al. (2009) Semantic search on digital document repositories based on text mining results. In: International Conferences on Digital Libraries and the Semantic Web 2009 (ICSD2009).